Errors in general practice: development of an error classification and pilot study of a method for detecting errors

Qual Saf Health Care. 2003 Dec;12(6):443-7. doi: 10.1136/qhc.12.6.443.

Abstract

Objective: To describe a classification of errors and to assess the feasibility and acceptability of a method for recording staff reported errors in general practice.

Design: An iterative process in a pilot practice was used to develop a classification of errors. This was incorporated in an anonymous self-report form which was then used to collect information on errors during June 2002. The acceptability of the reporting process was assessed using a self-completion questionnaire.

Setting: UK general practice.

Participants: Ten general practices in the North East of England.

Main outcome measures: Classification of errors, frequency of errors, error rates per 1000 appointments, acceptability of the process to participants.

Results: 101 events were used to create an initial error classification. This contained six categories: prescriptions, communication, appointments, equipment, clinical care, and "other" errors. Subsequently, 940 errors were recorded in a single 2 week period from 10 practices, providing additional information. 42% (397/940) were related to prescriptions, although only 6% (22/397) of these were medication errors. Communication errors accounted for 30% (282/940) of errors and clinical errors 3% (24/940). The overall error rate was 75.6/1000 appointments (95% CI 71 to 80). The method of error reporting was found to be acceptable by 68% (36/53) of respondents with only 8% (4/53) finding the process threatening.

Conclusion: We have developed a classification of errors and described a practical and acceptable method for reporting them that can be used as part of the process of risk management. Errors are common and, although all have the potential to lead to an adverse event, most are administrative.

MeSH terms

  • Attitude of Health Personnel*
  • England
  • Family Practice / standards*
  • Feasibility Studies
  • Forms and Records Control*
  • Humans
  • Medical Errors / classification*
  • Medical Errors / statistics & numerical data
  • Pilot Projects
  • Risk Management
  • Surveys and Questionnaires